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Discover why our Generative AI powered Knowledge Assistant is more powerful than AI Agent Assist tools
With Posh’s advanced and scalable artificial intelligence (AI) solutions for the banking sector, you can optimize customer service call center operations, enhance the customer experience, accelerate business growth while reducing costs, and ensure 24/7 financial services.
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Posh’s virtual assistants for financial institutions leverage generative and conversational AI technology to elevate customer satisfaction, increase operational efficiency, and boost ROI.
Discover the benefits of AI in the banking industry:
Customer-assisted AI through voice and digital channels provides immediate responses and simplifies the banking experience.
Employee-assisted generative AI through Knowledge Assistant offers immediate answers for live interactions.
Offers 24/7 service for routine questions.
Eliminates wait times for customer inquiries.
Reduces average handle time.
Accelerate employee onboarding and training times.
Save time for deeper customer engagement and business growth.
Eliminate third-party call centers.
Meet rising call volumes without extra staff.
Utilizing Posh’s tools powered by AI, our financial institution clients have experienced extraordinary success. We’ve helped countless financial institutions:
This comprehensive voice AI banking concierge acts as your virtual assistant, available 24/7 with 0 wait time. Our AI chatbot can greet callers, handle FAQs, provide seamless banking by phone, and, if you’d like, also process transactions and verify caller identities autonomously to prevent fraudulent activity.
When a customer interaction requires live agent assistance, our intelligent routing technology efficiently directs calls to the appropriate destination, equipping agents with essential background information. This configurable solution is tailored to suit your bank's specific needs and customer preferences. Eliminate abandonment and meet rising call volumes.
Empower your teams with rapid and effective information access. Cut through information overload and deliver precise answers in seconds. Reduce onboarding time, boost efficiency and improve ROI leading to a better employee and customer experience.
The Knowledge Assistant streamlines employees' daily work by connecting to your knowledge base. Instead of manually searching or messaging peers, the AI offers instant answers through a user-friendly conversational interface. This centralized platform grants all employees access to knowledge, democratizing information and eliminating the risk of relying on key individuals.
Discover the power of our AI-driven assistant specialized in the banking sector. Automate your frontline customer service with our AI chatbot, equipped to handle customer inquiries 24/7 with intelligent hand-off to live agents when necessary.
Built on the ability to answer over a thousand customer inquiries, it efficiently addresses questions without human intervention. Our Digital Assistant can live on your website and within online and mobile banking. Customize the chatbot to align perfectly with your brand, review every chat transcript, and harness data insights to continuously improve performance.
Discover the unique competitive advantages we provide for our banking sector clients:
At Posh, we recognize the limitless potential of AI, and we aim to harness that power on behalf of the banking industry. Our AI assistants utilize natural language processing based on real-world banking interactions to deliver seamless customer interactions every time.
Want to learn more about the use of AI and, more specifically, conversational and generative AI in banking? Check out this blog, and here are a few FAQs:
Conversational AI combines the foundations of natural language processing and machine learning to mimic human interactions. This kind of AI model is trained on large data sets with human input, conversations, user queries, and responses to recognize speech or text, understand it, and answer user questions.
Generative artificial intelligence is trained on different data sets to learn to recognize patterns. In a generative AI model, the goal is to produce “new” content based on these predictive patterns and synthesized from the training data.
A large language model (LLM) is typically built using deep learning techniques and neural networks. They are trained with a vast amount of text data to perform a wide range of natural language processing tasks, such as understanding and generating human language text. Due to these capabilities, LLMs enable a conversation with a user in a more “natural” way than older generations of AI technology.
